{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T11:57:12Z","timestamp":1785585432723,"version":"3.56.0"},"reference-count":23,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Synovial fluid examination is vital for diagnosing joint diseases in dogs. However, conventional manual methods are labor-intensive and prone to imprecision. Pretreating synovial fluid with hyaluronidase and utilizing an automated analyzer may enhance the accuracy, precision, and efficiency of synovial fluid analysis, particularly in dogs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aims and Objectives:<\/jats:title>\n                    <jats:p>This study aimed to assess the accuracy, precision, and efficiency of automated analyzer compared with manual cell count (MC) for analyzing synovial fluid in dogs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods:<\/jats:title>\n                    <jats:p>Fifty-two synovial fluid samples with varying cellularity were evaluated for the total nucleated cell count (TNCC) and differential cell count using three methods: hyaluronidase-treated automated cell count (AC-Hy), hyaluronidase-treated MC (MC-Hy), and untreated MC. The accuracy and precision of each method were statistically compared.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>AC-Hy and MC-Hy provide the strongest agreement in determining TNCC (mean difference: 23.92%, 95% confidence interval: \u221253.23%\u2013101.07%), with AC-Hy exhibiting the highest precision (coefficient of variations [CV]: 4.42%\u20134.49%). For differential counts, AC-Hy performed well in high TNCC samples (CV: 0.74%\u20132.25%) but was less reliable in low TNCC samples. MC-Hy, however, demonstrated consistent accuracy in determining differential count across all TNCC levels and produced superior smear quality compared with MC. In addition, AC-Hy offers shorter analytical times and is technically more efficient.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>In conclusion, pretreating canine synovial fluid with hyaluronidase enhances the accuracy and precision of synovial fluid analysis. While an automated analyzer enables rapid TNCC measurement, its reliability for differential counts decreases at low TNCC. Integrating automated count with hyaluronidase-treated manual differential counts and clinical evaluations would enhance diagnostic precision.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/ijvsm.ijvsm_6_26","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T13:00:39Z","timestamp":1784206839000},"update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Accuracy and Efficiency of Canine Synovial Fluid Analysis with Hyaluronidase Pretreatment and Automated Analyzer"],"prefix":"10.4103","volume":"14","author":[{"given":"Winda Kusuma","family":"Dewi","sequence":"first","affiliation":[{"name":"International Graduate Program, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Araya","family":"Radtanakatikanon","sequence":"additional","affiliation":[{"name":"Department of Veterinary 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